Book Image

Apache Hadoop 3 Quick Start Guide

By : Hrishikesh Vijay Karambelkar
Book Image

Apache Hadoop 3 Quick Start Guide

By: Hrishikesh Vijay Karambelkar

Overview of this book

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.
Table of Contents (10 chapters)

Summary

In this chapter, we have took a deep dive into HDFS. We tried to figure out how HDFS works and its key features. We looked at different data flow patterns of HDFS, where we can see HDFS in different roles. This was supported with various configuration files of HDFS and key attributes. We also looked at various command-line interface commands for HDFS and the Hadoop shell. Finally, we looked at the data structures that are used by HDFS with some examples.

In the next chapter, we will study the creation of a new MapReduce application with Apache Hadoop MapReduce.